Skip to contents

Plot Per-Actor Sequences From an htna Network

Source: R/sequence_plot_htna.R
sequence_plot_htna.Rd

Extracts each actor's events from the combined wide sequence in net$data (using net$node_groups as the node-to-actor lookup), compresses each session into the actor's own ordered events, pads to a common width, and renders with Nestimate::sequence_plot() grouped by actor. Each session contributes one row per actor that had at least one event in it.

Usage

sequence_plot_htna(
  net,
  by = c("state", "group"),
  type = c("index", "heatmap", "distribution"),
  grouped_legend = TRUE,
  ...
)

# S3 method for class 'htna'
plot_sequences(x, ...)

Arguments

net

An htna network from build_htna(). Must have $data and $node_groups populated.

by

"state" (default) keeps state-level colouring with one row per (session, actor) extracted from net$data; "group" re-colours the original combined session matrix by actor (each cell = the actor that acted at that time step).

type

Sequence plot layout: "index" (default; one panel per actor, vertically stacked), "heatmap" (single carpet with a white separator at the actor boundary, controllable via k_line_width), or "distribution" (one stacked-area panel per actor).

grouped_legend

Logical. If TRUE (default) and by = "state", the per-state legend is split into one block per actor with the actor name as a sub-title.

...

Forwarded to Nestimate::sequence_plot().

x

Same as net; used when calling via the plot_sequences() generic.

Value

Invisibly, the list returned by Nestimate::sequence_plot().

See also

Nestimate::sequence_plot(), build_htna().

Examples

# \donttest{
data(human_ai)
net <- build_htna(human_ai, actor_type = "actor_type")
#> Warning: A network with one long sequence is not recommended and can't be validated using bootstrap and other confirmatory testings.
#> Metadata aggregated per session: ties resolved by first occurrence in 'session_date' (1 sessions), 'cluster' (42 sessions), 'actor_type' (24 sessions)

sequence_plot_htna(net)                       # index, faceted

sequence_plot_htna(net, type = "heatmap")     # single carpet, white gulf

sequence_plot_htna(net, type = "distribution")

# }